Análisis de llamadas de agente de video de BeyondPresence con AI y Google Sheets

• •Punto final de HTTP Webhook (n8n generará automáticamente)
• •Credenciales de API de Google Sheets
• •Clave de API de OpenAI

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  "name": "BeyondPresence Video Agent Call Analytics with AI & Google Sheets",
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        "content": "## 🎥 BeyondPresence Webhook Trigger\n\nThis workflow is triggered when a BeyondPresence video agent call ends. The webhook receives comprehensive call data including:\n\n- Call metadata (participant, duration, timestamps)\n- Complete conversation transcript\n- Initial sentiment analysis\n- Call evaluation metrics\n\nMake sure to configure the webhook URL in your BeyondPresence dashboard under Settings → Webhooks"
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        "content": "## 🔍 Data Validation & AI Analysis\n\n1. **Validate & Enrich Data**: Ensures webhook data integrity and adds calculated fields\n2. **AI Call Analysis**: Uses OpenAI/OpenRouter to generate comprehensive call summary\n3. **Parse AI Response**: Extracts structured JSON from AI response with error handling\n\nThe AI analyzes:\n- Main discussion points\n- Action items & follow-ups\n- Sentiment analysis\n- Key decisions made\n- Questions raised"
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        "content": "## 📊 Google Sheets Setup\n\n**Quick Start**:\n1. Copy our template sheet:  https://docs.google.com/spreadsheets/d/1TO6-jkCtoSFNLJObtN0UyklgdUd3ZxEnUaNvUaBjpvo/copy\n2. After copying, get your new sheet's ID from the URL\n3. Update the Google Sheets node with your ID\nThe template includes all required columns and sample data!"
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                      "type": "string",
                      "operation": "equals"
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                    "leftValue": "={{ $json.body.event_type }}",
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        "jsCode": "// Validate incoming webhook data\nconst data = $input.first().json.body;\nconst errors = [];\n\n// Check required fields\nif (!data.event_type) errors.push(\"Missing event_type\");\nif (!data.call_id) errors.push(\"Missing call_id\");\nif (!data.call_data) errors.push(\"Missing call_data\");\nif (!data.messages || !Array.isArray(data.messages)) errors.push(\"Missing or invalid messages array\");\n\n// Validate call_data structure\nif (data.call_data) {\n  if (!data.call_data.userName) errors.push(\"Missing userName in call_data\");\n  if (!data.call_data.startedAt) errors.push(\"Missing startedAt timestamp\");\n  if (!data.call_data.endedAt) errors.push(\"Missing endedAt timestamp\");\n}\n\n// If there are errors, throw with details\nif (errors.length > 0) {\n  throw new Error(\"Validation failed: \" + errors.join(\", \"));\n}\n\n// Add calculated fields\nconst startTime = new Date(data.call_data.startedAt);\nconst endTime = new Date(data.call_data.endedAt);\nconst durationMs = endTime - startTime;\nconst durationMinutes = durationMs / 60000;\n\n// Return enriched data\nreturn [{\n  json: {\n    body: data,\n    validation: {\n      isValid: true,\n      timestamp: new Date().toISOString()\n    },\n    calculated: {\n      durationMinutes: durationMinutes.toFixed(2),\n      durationFormatted: formatDuration(durationMs),\n      dayOfWeek: startTime.toLocaleDateString('en-US', { weekday: 'long' }),\n      timeOfDay: getTimeOfDay(startTime),\n      messageCount: data.messages.length,\n      hasActionItems: checkForActionItems(data.messages)\n    }\n  }\n}];\n\n// Helper functions\nfunction formatDuration(ms) {\n  const seconds = Math.floor(ms / 1000);\n  const minutes = Math.floor(seconds / 60);\n  const remainingSeconds = seconds % 60;\n  return `${minutes}m ${remainingSeconds}s`;\n}\n\nfunction getTimeOfDay(date) {\n  const hour = date.getHours();\n  if (hour < 6) return \"Early Morning\";\n  if (hour < 12) return \"Morning\";\n  if (hour < 17) return \"Afternoon\";\n  if (hour < 21) return \"Evening\";\n  return \"Night\";\n}\n\nfunction checkForActionItems(messages) {\n  const actionKeywords = ['will do', 'action item', 'follow up', 'next step', 'todo', 'task'];\n  return messages.some(msg => \n    actionKeywords.some(keyword => \n      msg.message.toLowerCase().includes(keyword)\n    )\n  );\n}"
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              "role": "system",
              "content": "=You are an expert conversation analyst. Analyze the following call data and provide a comprehensive summary.\n\nCONTEXT:\n- Current Date/Time: {{ $now }}\n- Participant: {{ $json.body.call_data.userName }}\n- Call Duration: {{ $json.calculated.durationMinutes }} minutes\n- Time of Day: {{ $json.calculated.timeOfDay }}\n- Day of Week: {{ $json.calculated.dayOfWeek }}\n- Message Count: {{ $json.calculated.messageCount }}\n\nCONVERSATION DATA:\n{{ $json.body.messages.map(m => `[${m.sent_at}] ${m.sender.toUpperCase()}: ${m.message}`).join('\\n') }}\n\nANALYSIS REQUIREMENTS:\n1. Extract factual information only from the provided data\n2. If a section has no relevant content, use \"Not applicable\"\n3. Identify specific commitments, dates, and actions mentioned\n4. Analyze emotional tone and engagement level\n5. Note any technical issues or interruptions\n\nOUTPUT FORMAT (strict JSON):\n```json\n{\n  \"title\": \"Brief, descriptive title (max 80 chars)\",\n  \"metadata\": {\n    \"participant\": \"exact name from data\",\n    \"date\": \"ISO format date\",\n    \"duration_minutes\": \"number as string\",\n    \"topic\": \"main discussion topic\",\n    \"user_sentiment\": \"satisfied/neutral/dissatisfied\",\n    \"engagement_level\": \"high/medium/low\"\n  },\n  \"summary\": \"2-3 sentence executive summary of the conversation\",\n  \"main_points\": [\"up to 5 key discussion points\"],\n  \"action_items\": [\n    {\"task\": \"specific action\", \"owner\": \"person responsible\", \"due_date\": \"ISO date or TBD\"}\n  ],\n  \"follow_ups\": [\"specific next steps mentioned\"],\n  \"key_decisions\": [\"decisions made during call\"],\n  \"questions_raised\": [\"unresolved questions\"],\n  \"stories\": [\"any anecdotes or examples shared\"],\n  \"references\": [\"external resources or documents mentioned\"],\n  \"arguments\": [\n    {\"point\": \"argument made\", \"counterpoint\": \"opposing view if any\"}\n  ],\n  \"related_topics\": [\"topics that came up in discussion\"],\n  \"sentiment_analysis\": {\n    \"overall\": \"positive/neutral/negative\",\n    \"confidence\": \"high/medium/low\",\n    \"turning_points\": [\"moments where sentiment changed\"],\n    \"key_emotional_indicators\": [\"specific phrases indicating emotion\"]\n  },\n  \"recommendations\": [\"suggested actions based on analysis\"]\n}\n```\n\nRules:\n1. Use ONLY data from the provided conversation\n2. For empty sections, use empty arrays [] or \"Not applicable\"\n3. All dates should be in ISO 8601 format\n4. Be specific and actionable in recommendations"
            },
            {
              "content": "=Analyze this BeyondPresence video agent call:\n\nCall Data: {{ JSON.stringify($json.body.call_data) }}\nEvaluation: {{ JSON.stringify($json.body.evaluation) }}\nMessages: {{ JSON.stringify($json.body.messages) }}\n\nProvide the analysis in the exact JSON format specified."
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            "Date": "={{ $json.metadata.date }}",
            "Title": "={{ $json.title }}",
            "Topic": "={{ $json.metadata.topic }}",
            "Summary": "={{ $json.summary }}",
            "Follow Up 1": "={{ $json.follow_ups[0] || '' }}",
            "Follow Up 2": "={{ $json.follow_ups[1] || '' }}",
            "Participant": "={{ $json.metadata.participant }}",
            "Reference 1": "={{ $json.references[0] || '' }}",
            "Reference 2": "={{ $json.references[1] || '' }}",
            "Action Due 1": "={{ $json.action_items[0]?.due_date || '' }}",
            "Action Due 2": "={{ $json.action_items[1]?.due_date || '' }}",
            "Main Point 1": "={{ $json.main_points[0] || '' }}",
            "Main Point 2": "={{ $json.main_points[1] || '' }}",
            "Main Point 3": "={{ $json.main_points[2] || '' }}",
            "Processed At": "={{ $now.toISO() }}",
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            "Action Item 2": "={{ $json.action_items[1]?.task || '' }}",
            "Story/Example": "={{ $json.stories[0] || '' }}",
            "Action Owner 1": "={{ $json.action_items[0]?.owner || '' }}",
            "Action Owner 2": "={{ $json.action_items[1]?.owner || '' }}",
            "Key Decision 1": "={{ $json.key_decisions[0] || '' }}",
            "Key Decision 2": "={{ $json.key_decisions[1] || '' }}",
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            "Related Topic 1": "={{ $json.related_topics[0] || '' }}",
            "Related Topic 2": "={{ $json.related_topics[1] || '' }}",
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            "Question Raised 2": "={{ $json.questions_raised[1] || '' }}",
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          "mode": "list",
          "value": "gid=0"
        },
        "documentId": {
          "__rl": true,
          "mode": "list",
          "value": "",
          "cachedResultUrl": "",
          "cachedResultName": "Select your copied sheet"
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        "content": "## 🚨 Error Handling (Optional)\n\nAdd this error trigger to handle failures gracefully:\n- Log errors to a separate sheet\n- Send notifications to admins\n- Retry failed operations\n\nConnect to any node that might fail"
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      "typeVersion": 1
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      "parameters": {
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        "content": "## 🔔 Optional Extensions\n\n**Slack Notification**:\n- Send summary to team channel\n- Alert on negative sentiment\n- Notify about action items\n\n**Database Backup**:\n- Store in PostgreSQL/MySQL\n- Enable advanced analytics\n- Create dashboards\n\n**CRM Integration**:\n- Update contact records\n- Create follow-up tasks\n- Log call activities"
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